Cognitive Radio technology holds great promise in solving the problem of spectrum scarcity.A plethora of routing protocols exist for Cognitive Radio networks,however most of them relay on establishing an end-to-end path using a Common Control Channel.This paper focuses on scenarios where the Primary User traffic is very high and erratic and therefore trying to set up end-to-end paths is not feasible.A novel solution to this problem is proposed where the cognitive users form a Cognitive Delay Tolerant Network through a modification in the network stack.Well researched delay tolerant networking routing protocols designed for networks with unreliable links, configured for multiple channel can used for routing in high primary user traffic environments.Through extensive simulation we show the that proposed architecture provides very high delivery ratio (close to 1) in the presence of very high primary user traffic with negligible computational complexity and the absence of a common control channel. We also show that trying to rely on routing protocols that try to establish end to end paths such as Multi-Channel AODV is not feasible. The performance of Multi-Channel AODV and proposed architecture is compared and analyzed with bundle/packet delivery ratio, end-to-end delay and hop count as performance metrics.
Content caching is an efficient technique to reduce delivery latency and system congestion during peak-traffic times by bringing data closer to end users. Existing works on caching usually assume symmetric networks with identical user requests distribution, which might be in contrast to practical scenarios where the number of users is usually arbitrary. In this paper, we investigate a cache-assisted heterogeneous network in which edge nodes or base stations (BSs) are capable of storing content data in their local cache. We consider general practical scenarios where each edge node is serving an arbitrary number of users. First, we derive an optimal storage allocation over the BSs to minimize the shared backhaul throughput for a uncoded caching policy. Second, a novel coded caching strategy is proposed to further reduce the shared backhaul's load. Finally, the effectiveness of our proposed caching strategy is demonstrated via numerical results.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.